Based on the Recency Effect in Behavioral Finance, why can't we use reformat this bias and use the information at our finger tips to be more effective in our prediction of outcomes? Given the recent trends in the market with GME, AMC and others, now is the perfect time to analyze what people are saying

What it does

Taking a weeks worth of posts and comments, I identified what stocks or companies were talking about on r/investing and then utilized that data to fuel a sentiment analysis. From there knowing the most positive and negative stocks, I tested various ML models to model market movement. Finally the goal was to visualize the results using a Front end framework but given the time limit and limit on manpower I did not finish!

How I built it

I did the analysis, model building all within Jupyter Notebooks using python. I was using React and Javascript for the front end.

Challenges I ran into

Coming from a data analysis background, I was fairly familiar with model building and data cleaning, but accessing APIs and using React with Javascript for the very first time definitely proved to be killer in terms of development time. I also wish I had more time to properly analyze and tune my models. I think my RNN could be improved significantly.

Accomplishments that I'm proud of

I learned how to start to build a React App! And I finally got away from using csv files to get my data. I can't wait to combine all these skills together and build end-to-end applications for data science / machine learning!

What I learned

I learned Javascript, React, and how to access an API. I also learned that you have to stay concentrated on small sprints of work and commitments to having an MVP. I was so focused at one point in solving a data wrangling issue that I had wasted a few hours rather than working with what I had

What's next for Sentiment Stock Dashboard

I will definitely be completely the front end portion of this and tuning the analysis portion. Given my background I should have no excuse in not having the RNN working the way it should (could be a data issue though)!! Cheers!

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